Overview

Brought to you by YData

Dataset statistics

Number of variables12
Number of observations2779
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory260.7 KiB
Average record size in memory96.0 B

Variable types

Numeric11
Categorical1

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
Compactness is highly overall correlated with Extent and 2 other fieldsHigh correlation
Extent is highly overall correlated with Compactness and 1 other fieldsHigh correlation
Roundness is highly overall correlated with cluster and 1 other fieldsHigh correlation
Solidity is highly overall correlated with Compactness and 1 other fieldsHigh correlation
cluster is highly overall correlated with RoundnessHigh correlation
cluster_average_Type is highly overall correlated with Compactness and 1 other fieldsHigh correlation
cluster has 703 (25.3%) zeros Zeros

Reproduction

Analysis started2024-12-17 00:47:18.245186
Analysis finished2024-12-17 00:47:34.886938
Duration16.64 seconds
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

Length
Real number (ℝ)

Distinct1928
Distinct (%)69.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean289.79613
Minimum151.33527
Maximum515.35248
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2024-12-17T02:47:35.020524image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum151.33527
5-th percentile204.02749
Q1244.91535
median279.86469
Q3329.1411
95-th percentile411.28687
Maximum515.35248
Range364.01721
Interquartile range (IQR)84.225746

Descriptive statistics

Standard deviation62.077123
Coefficient of variation (CV)0.21420963
Kurtosis0.054655934
Mean289.79613
Median Absolute Deviation (MAD)39.903961
Skewness0.6377387
Sum805343.46
Variance3853.5692
MonotonicityNot monotonic
2024-12-17T02:47:35.203579image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
254.4638672 5
 
0.2%
241.2635498 5
 
0.2%
252.4578857 5
 
0.2%
281.8874512 4
 
0.1%
252.1556091 4
 
0.1%
231.7611084 4
 
0.1%
269.8413696 4
 
0.1%
269.6526184 4
 
0.1%
168.7080231 4
 
0.1%
328.9320374 4
 
0.1%
Other values (1918) 2736
98.5%
ValueCountFrequency (%)
151.3352661 1
 
< 0.1%
154.7952423 2
0.1%
156.0432281 1
 
< 0.1%
156.4661713 1
 
< 0.1%
159.2402954 1
 
< 0.1%
159.8836517 1
 
< 0.1%
160.4595642 1
 
< 0.1%
160.5242767 2
0.1%
167.8253021 3
0.1%
168.6890869 1
 
< 0.1%
ValueCountFrequency (%)
515.352478 1
< 0.1%
512.6253052 2
0.1%
506.372406 1
< 0.1%
499.4121399 1
< 0.1%
497.4573059 1
< 0.1%
481.2356873 1
< 0.1%
477.2573853 1
< 0.1%
475.8347168 1
< 0.1%
469.9933167 1
< 0.1%
468.4328918 2
0.1%

Width
Real number (ℝ)

Distinct1849
Distinct (%)66.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean170.80019
Minimum88.050529
Maximum258.56979
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2024-12-17T02:47:35.369409image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum88.050529
5-th percentile126.40553
Q1149.59875
median169.92412
Q3190.57055
95-th percentile224.64789
Maximum258.56979
Range170.51926
Interquartile range (IQR)40.971794

Descriptive statistics

Standard deviation29.561715
Coefficient of variation (CV)0.17307776
Kurtosis-0.03847341
Mean170.80019
Median Absolute Deviation (MAD)20.548431
Skewness0.19821804
Sum474653.74
Variance873.895
MonotonicityNot monotonic
2024-12-17T02:47:35.537282image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
169.46492 5
 
0.2%
184.4487152 5
 
0.2%
129.9219666 4
 
0.1%
162.4747772 4
 
0.1%
206.7833099 4
 
0.1%
153.9707642 4
 
0.1%
167.6368713 4
 
0.1%
191.330368 4
 
0.1%
153.7546997 4
 
0.1%
175.6868896 4
 
0.1%
Other values (1839) 2737
98.5%
ValueCountFrequency (%)
88.05052948 1
< 0.1%
88.05123138 2
0.1%
90.07479095 1
< 0.1%
90.56969452 1
< 0.1%
92.25747681 1
< 0.1%
92.62679291 2
0.1%
93.73306274 2
0.1%
93.8094101 2
0.1%
94.20102692 1
< 0.1%
94.51618195 2
0.1%
ValueCountFrequency (%)
258.5697937 1
< 0.1%
257.7919006 1
< 0.1%
257.3881836 1
< 0.1%
256.3813782 1
< 0.1%
255.9151306 1
< 0.1%
254.0734253 1
< 0.1%
253.7433777 1
< 0.1%
253.3808289 1
< 0.1%
253.0660858 1
< 0.1%
251.3216553 1
< 0.1%

Area
Real number (ℝ)

Distinct2726
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26501.021
Minimum6037
Maximum89282
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2024-12-17T02:47:35.703528image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum6037
5-th percentile10598.6
Q116220
median23401.5
Q333379.25
95-th percentile54401.25
Maximum89282
Range83245
Interquartile range (IQR)17159.25

Descriptive statistics

Standard deviation13782.98
Coefficient of variation (CV)0.52009242
Kurtosis1.651996
Mean26501.021
Median Absolute Deviation (MAD)7960
Skewness1.2484165
Sum73646338
Variance1.8997055 × 108
MonotonicityNot monotonic
2024-12-17T02:47:35.853466image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10535 3
 
0.1%
13978 2
 
0.1%
22004 2
 
0.1%
34304.5 2
 
0.1%
14842 2
 
0.1%
27715 2
 
0.1%
17510.5 2
 
0.1%
10869.5 2
 
0.1%
27225.5 2
 
0.1%
13893 2
 
0.1%
Other values (2716) 2758
99.2%
ValueCountFrequency (%)
6037 1
< 0.1%
6177 1
< 0.1%
6185 1
< 0.1%
6198.5 1
< 0.1%
6499.5 2
0.1%
6574.5 1
< 0.1%
6755 1
< 0.1%
6819.5 1
< 0.1%
6898 1
< 0.1%
6915.5 1
< 0.1%
ValueCountFrequency (%)
89282 1
< 0.1%
86040 1
< 0.1%
85880 1
< 0.1%
83822 1
< 0.1%
81813 1
< 0.1%
79559 1
< 0.1%
78531.5 1
< 0.1%
78338.5 1
< 0.1%
78242 1
< 0.1%
77816.5 1
< 0.1%

Roundness
Real number (ℝ)

High correlation 

Distinct1931
Distinct (%)69.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.46989785
Minimum0.17374846
Maximum0.68557706
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2024-12-17T02:47:36.020056image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.17374846
5-th percentile0.25493619
Q10.38462395
median0.47143167
Q30.57744222
95-th percentile0.63809043
Maximum0.68557706
Range0.5118286
Interquartile range (IQR)0.19281827

Descriptive statistics

Standard deviation0.11821081
Coefficient of variation (CV)0.25156703
Kurtosis-0.8825995
Mean0.46989785
Median Absolute Deviation (MAD)0.097516954
Skewness-0.298612
Sum1305.8461
Variance0.013973795
MonotonicityNot monotonic
2024-12-17T02:47:36.202055image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6323167105 7
 
0.3%
0.4142495572 5
 
0.2%
0.2295774345 4
 
0.1%
0.3864994768 4
 
0.1%
0.2231981525 4
 
0.1%
0.3864353386 4
 
0.1%
0.4591370937 4
 
0.1%
0.3682207855 4
 
0.1%
0.4947791534 4
 
0.1%
0.5100017618 4
 
0.1%
Other values (1921) 2735
98.4%
ValueCountFrequency (%)
0.1737484552 2
0.1%
0.1783044211 1
< 0.1%
0.1881483404 1
< 0.1%
0.1943163767 2
0.1%
0.194803299 2
0.1%
0.2021449064 2
0.1%
0.2048341426 1
< 0.1%
0.2133799222 1
< 0.1%
0.2134423226 1
< 0.1%
0.2137339949 1
< 0.1%
ValueCountFrequency (%)
0.6855770595 1
< 0.1%
0.6803785287 2
0.1%
0.6793269392 1
< 0.1%
0.6773676637 1
< 0.1%
0.6764886335 2
0.1%
0.6741675939 1
< 0.1%
0.673256447 1
< 0.1%
0.6706803041 2
0.1%
0.6688671059 1
< 0.1%
0.6684887697 1
< 0.1%

Solidity
Real number (ℝ)

High correlation 

Distinct2776
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.95636796
Minimum0.71877246
Maximum0.99288912
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2024-12-17T02:47:36.341009image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.71877246
5-th percentile0.87472346
Q10.94491857
median0.97055983
Q30.9815312
95-th percentile0.98863799
Maximum0.99288912
Range0.27411666
Interquartile range (IQR)0.036612625

Descriptive statistics

Standard deviation0.038466695
Coefficient of variation (CV)0.040221647
Kurtosis5.1951529
Mean0.95636796
Median Absolute Deviation (MAD)0.013996964
Skewness-2.1237772
Sum2657.7466
Variance0.0014796866
MonotonicityNot monotonic
2024-12-17T02:47:36.503311image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.7187724634 2
 
0.1%
0.9258937078 2
 
0.1%
0.9685987384 2
 
0.1%
0.9426886499 1
 
< 0.1%
0.9430423355 1
 
< 0.1%
0.9460082822 1
 
< 0.1%
0.9364214116 1
 
< 0.1%
0.9400149134 1
 
< 0.1%
0.9425563276 1
 
< 0.1%
0.9153351932 1
 
< 0.1%
Other values (2766) 2766
99.5%
ValueCountFrequency (%)
0.7187724634 2
0.1%
0.7511175547 1
< 0.1%
0.7671826431 1
< 0.1%
0.7841960295 1
< 0.1%
0.7853451096 1
< 0.1%
0.7869588356 1
< 0.1%
0.7880165477 1
< 0.1%
0.7882394273 1
< 0.1%
0.788433273 1
< 0.1%
0.7889663934 1
< 0.1%
ValueCountFrequency (%)
0.992889123 1
< 0.1%
0.9927057971 1
< 0.1%
0.9924222343 1
< 0.1%
0.9922863139 1
< 0.1%
0.992081448 1
< 0.1%
0.9920251382 1
< 0.1%
0.9919179942 1
< 0.1%
0.9919061562 1
< 0.1%
0.9918980822 1
< 0.1%
0.9918912921 1
< 0.1%

Compactness
Real number (ℝ)

High correlation 

Distinct2776
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.811523
Minimum1.1644687
Maximum6.825684
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2024-12-17T02:47:36.653153image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.1644687
5-th percentile1.2482719
Q11.356854
median1.5761014
Q31.9595166
95-th percentile3.311198
Maximum6.825684
Range5.6612152
Interquartile range (IQR)0.60266268

Descriptive statistics

Standard deviation0.74660938
Coefficient of variation (CV)0.41214458
Kurtosis10.115578
Mean1.811523
Median Absolute Deviation (MAD)0.25896693
Skewness2.8195989
Sum5034.2224
Variance0.55742557
MonotonicityNot monotonic
2024-12-17T02:47:36.811843image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.457891663 2
 
0.1%
2.452015431 2
 
0.1%
2.229812351 2
 
0.1%
1.660023385 1
 
< 0.1%
2.274092729 1
 
< 0.1%
2.207729603 1
 
< 0.1%
2.466474898 1
 
< 0.1%
2.14965433 1
 
< 0.1%
1.611830959 1
 
< 0.1%
1.844151746 1
 
< 0.1%
Other values (2766) 2766
99.5%
ValueCountFrequency (%)
1.164468727 1
< 0.1%
1.16746807 1
< 0.1%
1.171493171 1
< 0.1%
1.172427662 1
< 0.1%
1.175407185 1
< 0.1%
1.179803389 1
< 0.1%
1.180105672 1
< 0.1%
1.182508941 1
< 0.1%
1.183430673 1
< 0.1%
1.184406026 1
< 0.1%
ValueCountFrequency (%)
6.825683957 1
< 0.1%
6.732644849 1
< 0.1%
6.704805865 1
< 0.1%
6.596767535 1
< 0.1%
6.488794301 1
< 0.1%
6.457891663 2
0.1%
6.187797714 1
< 0.1%
6.182120222 1
< 0.1%
5.848393522 1
< 0.1%
5.724285705 1
< 0.1%

Aspect_Ratio
Real number (ℝ)

Distinct1001
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7535916
Minimum1.4000817
Maximum2.6073675
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2024-12-17T02:47:36.970118image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.4000817
5-th percentile1.5186864
Q11.6155819
median1.7059238
Q31.838599
95-th percentile2.1539618
Maximum2.6073675
Range1.2072859
Interquartile range (IQR)0.22301711

Descriptive statistics

Standard deviation0.20119633
Coefficient of variation (CV)0.11473386
Kurtosis1.7384901
Mean1.7535916
Median Absolute Deviation (MAD)0.10548497
Skewness1.2475569
Sum4873.231
Variance0.040479963
MonotonicityNot monotonic
2024-12-17T02:47:37.153434image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.548957718 8
 
0.3%
1.689471263 7
 
0.3%
1.864239083 7
 
0.3%
1.800293087 7
 
0.3%
2.111400983 7
 
0.3%
1.577732151 7
 
0.3%
1.600438803 7
 
0.3%
1.767010353 7
 
0.3%
1.682902028 6
 
0.2%
1.711133054 6
 
0.2%
Other values (991) 2710
97.5%
ValueCountFrequency (%)
1.400081673 4
0.1%
1.427405508 5
0.2%
1.436017711 1
 
< 0.1%
1.449457939 2
 
0.1%
1.45116974 4
0.1%
1.452477741 3
0.1%
1.462166258 2
 
0.1%
1.464647005 2
 
0.1%
1.466764392 2
 
0.1%
1.468290452 4
0.1%
ValueCountFrequency (%)
2.607367523 1
 
< 0.1%
2.606582831 4
0.1%
2.598485293 2
0.1%
2.580846925 2
0.1%
2.579810661 3
0.1%
2.573946228 1
 
< 0.1%
2.527518166 4
0.1%
2.506223458 2
0.1%
2.468742797 2
0.1%
2.424797685 2
0.1%

Eccentricity
Real number (ℝ)

Distinct1000
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.81378082
Minimum0.71358195
Maximum0.93056271
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2024-12-17T02:47:37.303662image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.71358195
5-th percentile0.75262308
Q10.78470995
median0.81032867
Q30.83972226
95-th percentile0.88790298
Maximum0.93056271
Range0.21698076
Interquartile range (IQR)0.05501231

Descriptive statistics

Standard deviation0.041023664
Coefficient of variation (CV)0.050411195
Kurtosis-0.40592814
Mean0.81378082
Median Absolute Deviation (MAD)0.027338524
Skewness0.31553432
Sum2261.4969
Variance0.001682941
MonotonicityNot monotonic
2024-12-17T02:47:37.469389image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.7577382187 8
 
0.3%
0.799227214 7
 
0.3%
0.8133212007 7
 
0.3%
0.8664939375 7
 
0.3%
0.8340819394 7
 
0.3%
0.809647096 7
 
0.3%
0.8342153168 7
 
0.3%
0.8947935603 7
 
0.3%
0.8556213928 7
 
0.3%
0.7763410223 6
 
0.2%
Other values (990) 2709
97.5%
ValueCountFrequency (%)
0.7135819492 1
 
< 0.1%
0.7238922111 4
0.1%
0.724666961 2
 
0.1%
0.7252565525 2
 
0.1%
0.7295600553 2
 
0.1%
0.7306442431 4
0.1%
0.731564017 5
0.2%
0.7322237453 3
0.1%
0.7339825872 1
 
< 0.1%
0.7343088284 3
0.1%
ValueCountFrequency (%)
0.9305627139 2
0.1%
0.9235290021 4
0.1%
0.9234810453 2
0.1%
0.9229834746 1
 
< 0.1%
0.9218824365 4
0.1%
0.9218170052 3
0.1%
0.9214451377 2
0.1%
0.9184035118 2
0.1%
0.9169480017 1
 
< 0.1%
0.9142881235 2
0.1%

Extent
Real number (ℝ)

High correlation 

Distinct2776
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.72508688
Minimum0.46654269
Maximum0.81931639
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2024-12-17T02:47:37.620143image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.46654269
5-th percentile0.63285699
Q10.70214106
median0.73381696
Q30.75755057
95-th percentile0.78140518
Maximum0.81931639
Range0.35277369
Interquartile range (IQR)0.05540951

Descriptive statistics

Standard deviation0.045937742
Coefficient of variation (CV)0.063354811
Kurtosis1.9247756
Mean0.72508688
Median Absolute Deviation (MAD)0.026408593
Skewness-1.2135628
Sum2015.0164
Variance0.0021102761
MonotonicityNot monotonic
2024-12-17T02:47:37.803758image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5790716322 2
 
0.1%
0.6859948849 2
 
0.1%
0.6921828172 2
 
0.1%
0.697400762 1
 
< 0.1%
0.687406994 1
 
< 0.1%
0.6853117643 1
 
< 0.1%
0.6604774052 1
 
< 0.1%
0.7204512742 1
 
< 0.1%
0.7136798469 1
 
< 0.1%
0.6306057076 1
 
< 0.1%
Other values (2766) 2766
99.5%
ValueCountFrequency (%)
0.4665426918 1
< 0.1%
0.5260974521 1
< 0.1%
0.5262999181 1
< 0.1%
0.5306523297 1
< 0.1%
0.5312302749 1
< 0.1%
0.5337828196 1
< 0.1%
0.5375586854 1
< 0.1%
0.5390856561 1
< 0.1%
0.54468746 1
< 0.1%
0.5516964117 1
< 0.1%
ValueCountFrequency (%)
0.8193163857 1
< 0.1%
0.8150636943 1
< 0.1%
0.812721519 1
< 0.1%
0.8121424577 1
< 0.1%
0.8091220238 1
< 0.1%
0.8080778302 1
< 0.1%
0.8074948089 1
< 0.1%
0.8056143424 1
< 0.1%
0.8054523539 1
< 0.1%
0.8051935229 1
< 0.1%

Type
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.8 KiB
2
938 
0
922 
1
919 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2779
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
2 938
33.8%
0 922
33.2%
1 919
33.1%

Length

2024-12-17T02:47:37.976248image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-12-17T02:47:38.103508image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
2 938
33.8%
0 922
33.2%
1 919
33.1%

Most occurring characters

ValueCountFrequency (%)
2 938
33.8%
0 922
33.2%
1 919
33.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2779
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 938
33.8%
0 922
33.2%
1 919
33.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2779
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 938
33.8%
0 922
33.2%
1 919
33.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2779
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 938
33.8%
0 922
33.2%
1 919
33.1%

cluster
Real number (ℝ)

High correlation  Zeros 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4699532
Minimum0
Maximum5
Zeros703
Zeros (%)25.3%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2024-12-17T02:47:38.200227image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q35
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)5

Descriptive statistics

Standard deviation1.9721094
Coefficient of variation (CV)0.79844
Kurtosis-1.5469199
Mean2.4699532
Median Absolute Deviation (MAD)2
Skewness0.067025689
Sum6864
Variance3.8892157
MonotonicityNot monotonic
2024-12-17T02:47:38.320065image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5 776
27.9%
0 703
25.3%
1 413
14.9%
3 385
13.9%
2 296
 
10.7%
4 206
 
7.4%
ValueCountFrequency (%)
0 703
25.3%
1 413
14.9%
2 296
 
10.7%
3 385
13.9%
4 206
 
7.4%
5 776
27.9%
ValueCountFrequency (%)
5 776
27.9%
4 206
 
7.4%
3 385
13.9%
2 296
 
10.7%
1 413
14.9%
0 703
25.3%

cluster_average_Type
Real number (ℝ)

High correlation 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0058206
Minimum0.45833333
Maximum1.2509603
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2024-12-17T02:47:38.420082image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.45833333
5-th percentile0.45833333
Q10.88192771
median1.1678521
Q31.2509603
95-th percentile1.2509603
Maximum1.2509603
Range0.79262697
Interquartile range (IQR)0.3690326

Descriptive statistics

Standard deviation0.24609752
Coefficient of variation (CV)0.24467338
Kurtosis-0.55584077
Mean1.0058206
Median Absolute Deviation (MAD)0.083108245
Skewness-0.72756223
Sum2795.1754
Variance0.06056399
MonotonicityNot monotonic
2024-12-17T02:47:38.547311image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1.250960307 776
27.9%
1.167852063 703
25.3%
0.8819277108 413
14.9%
0.8837209302 385
13.9%
0.6910299003 296
 
10.7%
0.4583333333 206
 
7.4%
ValueCountFrequency (%)
0.4583333333 206
 
7.4%
0.6910299003 296
 
10.7%
0.8819277108 413
14.9%
0.8837209302 385
13.9%
1.167852063 703
25.3%
1.250960307 776
27.9%
ValueCountFrequency (%)
1.250960307 776
27.9%
1.167852063 703
25.3%
0.8837209302 385
13.9%
0.8819277108 413
14.9%
0.6910299003 296
 
10.7%
0.4583333333 206
 
7.4%

Interactions

2024-12-17T02:47:32.986712image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:18.798961image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:20.241215image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:21.806460image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:23.095747image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:24.473725image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:25.819374image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:27.170569image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:28.536974image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:29.893070image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:31.405066image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:33.136707image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:18.941178image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:20.572585image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:21.931865image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:23.217990image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:24.613029image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:25.936553image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:27.305080image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:28.660370image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:30.020197image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:31.569281image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:33.271613image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:19.070867image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:20.698684image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:22.052479image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:23.341963image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:24.737693image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:26.066373image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:27.431680image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:28.783797image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:30.136666image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:31.683138image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:33.383386image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:19.190486image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:20.801077image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:22.155184image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:23.446624image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:24.840236image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:26.170646image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:27.534451image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:28.886695image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:30.259505image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:32.084043image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:33.515257image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:19.335972image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:20.920369image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:22.281073image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:23.574793image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:24.953027image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:26.294753image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:27.653031image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:29.008069image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:30.386701image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:32.189344image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:33.639663image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:19.456378image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:21.058388image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:22.400572image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:23.705938image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:25.070887image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:26.407486image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:27.764245image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:29.196224image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:30.500605image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:32.299011image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:33.765128image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:19.588840image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:21.197772image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:22.526008image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:23.818747image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:25.205451image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:26.537881image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:27.897936image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:29.303422image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:30.641994image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:32.421022image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:33.870412image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:19.716836image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:21.315951image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:22.639427image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:23.929760image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:25.315687image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:26.653139image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:28.038161image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:29.419925image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:30.770037image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:32.536786image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:33.995553image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:19.844756image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:21.432843image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:22.754800image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:24.097310image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:25.433936image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:26.763306image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:28.150820image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:29.520008image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:30.886688image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:32.650646image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:34.143223image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:19.970562image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:21.568558image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:22.865768image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:24.220449image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:25.553685image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:26.915821image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:28.286422image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:29.649041image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:31.023849image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:32.770197image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:34.270128image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:20.096815image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:21.691596image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:22.969002image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:24.355997image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:25.674228image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:27.040844image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:28.407225image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:29.752861image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:31.207844image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-17T02:47:32.874068image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-12-17T02:47:38.657445image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
AreaAspect_RatioCompactnessEccentricityExtentLengthRoundnessSolidityTypeWidthclustercluster_average_Type
Area1.0000.0230.0730.0180.3540.4550.2310.1750.1800.2790.289-0.073
Aspect_Ratio0.0231.0000.1200.359-0.0470.146-0.202-0.0850.1910.023-0.033-0.363
Compactness0.0730.1201.0000.109-0.5190.178-0.433-0.8310.1940.126-0.186-0.506
Eccentricity0.0180.3590.1091.000-0.0360.121-0.203-0.0610.1730.012-0.282-0.291
Extent0.354-0.047-0.519-0.0361.0000.0300.2830.6750.257-0.0430.2110.316
Length0.4550.1460.1780.1210.0301.000-0.196-0.1020.2480.309-0.061-0.477
Roundness0.231-0.202-0.433-0.2030.283-0.1961.0000.3200.314-0.0230.5400.529
Solidity0.175-0.085-0.831-0.0610.675-0.1020.3201.0000.236-0.0450.1390.415
Type0.1800.1910.1940.1730.2570.2480.3140.2361.0000.1810.2540.248
Width0.2790.0230.1260.012-0.0430.309-0.023-0.0450.1811.000-0.264-0.227
cluster0.289-0.033-0.186-0.2820.211-0.0610.5400.1390.254-0.2641.0000.353
cluster_average_Type-0.073-0.363-0.506-0.2910.316-0.4770.5290.4150.248-0.2270.3531.000

Missing values

2024-12-17T02:47:34.436962image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-12-17T02:47:34.692415image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

LengthWidthAreaRoundnessSolidityCompactnessAspect_RatioEccentricityExtentTypeclustercluster_average_Type
0272.553253227.94062822619.00.4604670.9733841.4582651.5657950.7981470.681193001.167852
1340.942719234.18812623038.00.4519830.9573041.6018441.5529920.7552330.656353010.881928
2344.597992229.41861022386.50.1783040.9672701.4877721.6962360.8451510.683620010.881928
3367.850677232.76315322578.50.5479650.9655121.5409791.9425380.8061220.685360020.691030
4276.140106230.15074219068.00.4302720.9514501.6293952.1425030.8446230.714800030.883721
5315.898743231.91442919335.00.6056190.9573441.5586281.7403880.8142270.727920001.167852
6195.676468226.37104818583.50.3866790.9562861.6142122.1344060.8083270.727908030.883721
7227.627579226.18614218069.50.2576670.9689781.5064261.6884120.8767960.740675001.167852
8413.477173133.72895841492.00.3090090.9509862.2328341.7311570.7988280.767645010.881928
9418.210327156.35211240630.50.2957830.9558882.1160561.6471750.8221750.758598010.881928
LengthWidthAreaRoundnessSolidityCompactnessAspect_RatioEccentricityExtentTypeclustercluster_average_Type
2769294.598572133.20159925529.00.3745270.9562321.8260741.8094120.7903350.681719210.881928
2770282.113983213.36200021200.50.5478540.9451431.7720071.5081240.7677230.708573201.167852
2771420.821259206.78331020866.00.4874000.9544411.7328661.6908990.8413580.721807210.881928
2772292.296082207.03163120319.50.3119530.9455111.9572492.0703410.8571960.719325230.883721
2773345.911133206.84550520483.50.5919480.9584941.6709721.6560220.7960270.731972251.250960
2774244.866592192.70936618471.50.4569140.9310001.8389651.8128430.7621050.725739201.167852
2775366.171509186.25474517213.50.6424950.9527061.5642341.7058850.8101620.714016251.250960
2776408.806732186.19618217510.50.5581890.9488211.6817051.6680840.8221380.718999210.881928
2777280.646667188.66082817941.00.3864650.9448101.7647011.7059240.7972620.738191201.167852
2778269.356903176.02363636683.50.6437610.9473801.7079331.5302310.7569300.722429251.250960

Duplicate rows

Most frequently occurring

LengthWidthAreaRoundnessSolidityCompactnessAspect_RatioEccentricityExtentTypeclustercluster_average_Type# duplicates
0446.136932203.45167567056.00.4289550.9258942.4520152.192840.8899650.685995020.691032